1. Field of the Invention
The invention relates to a method and device for text improvement.
2. Description of the Related Art
The article “Thresholding and enhancement of text images for character recognition”, by W. W. Cindy Jiang, IEEE, Proceedings of the international conference on acoustics, speech, and signal processing (ICASSP), NY, vol. 20, 1995, pp. 2395–2398, discloses a scheme which converts graytone text images of low spatial resolution to bi-level images of higher spatial resolution for character recognition. A variable thresholding technique and morphological filtering are used. It is stated that most optical character recognition systems perform binarization of inputs before attempting recognition, and that text images are usually supposed to be binary.
The article “A segmentation method for composite text/graphics (halftone and continuous tone photographs) documents”, by S. Ochuchi et al., Systems and Computers in Japan, Vol. 24, No. 2, 1993, pp. 35–44, discloses that when processing composite documents for digital copy machines and facsimile which contain a mixture of text, halftone and continuous tone photographs, ideally, the text portion can be separated from the graphics portion and more efficiently represented than the multi-bit pixel bitmap graphics representation.
Nowadays, digital display devices are more and more frequently matrix devices, e.g., Liquid Crystal Displays, where each pixel is mapped on a location of the screen having a one-to-one relationship between raster data and display points. This technology implies the usage of a scaling system to change the format of the input video/graphic signal so that it satisfies the size of the device, i.e., the number of its pixels. The scaling block is based on a filter bank that performs pixel interpolation when the zooming factor is varying. Actually available solutions on the market apply an undifferentiated processing on the graphic raster that leads to results with unavoidable artifacts. Usually, low-pass filters reduce pixellation, also know as the seesaw effect, on diagonals, and prevent the signal from suffering from aliasing due to the sub-sampling, but they also introduce other annoying effects, such as, blurring the images. It depends on the content of the displayed signal, the relevance of the perceived artifacts and the kind of artifacts that have to be preferred as unavoidable.